Better real-time data for the country’s congested transmission lines

Jørgen Festervoll, CEO of Heimdall Power, is happy to be taking part in the biggest U.S. deployment to date of a technology that could dramatically expand the capacity of the country’s overstressed transmission grids. He also thinks the project is just scratching the surface. 

In March, the Norwegian company announced plans to deploy 52 of its sensors on the transmission lines of Minnesota-based cooperative utility Great River Energy. Those sensors provide grid operators with dynamic line ratings (DLR) — real-time data on how much power transmission lines can carry based on temperature, wind speeds, and other factors. 

More often than not, this data reveals that the traditional, conservative ​“static” ratings that grid operators now rely on are significantly underestimating how much electricity those lines can actually carry — on average by between 10 and 30 percent, and sometimes by 50 percent or more. 

Projects in Europe that use Heimdall’s Neuron sensors, as well as DLR technologies from a host of other providers, have produced these findings over the course of a decade. In the last five years or so, U.S. utilities have begun to follow the lead of their European counterparts, with pilot projects in New York state, Pennsylvania, Ohio, and Indiana showing similar results. 

Now, Festervoll wants to move past the stage at which a 52-sensor deployment represents a breakthrough for U.S. utilities. ​“That’s very small scale,” he said — and it doesn’t unlock the full value of what grid operators can do with the technology. 

Being able to run entire transmission networks with the real-time information DLR provides will allow grid operators to ​“bring more renewables online” and let big power users like data centers and factories ​“get connections much faster,” he said, citing two key bottlenecks for much of the overloaded U.S. transmission grid. ​“There will be positive economic benefits, and it will save money for ratepayers.” 

These potential benefits have made dynamic-line-rating systems and a host of other ​“grid-enhancing technologies” — GETs for short — a focus for regulators, policymakers, and government agencies looking for solutions to the country’s inadequate power grids. 

In an April report, the U.S. Department of Energy estimated that widely deployed DLR could increase existing grid capacity by roughly 80 gigawatts, saving billions of dollars in transmission infrastructure costs. The Biden administration has set a goal of deploying GETs across 100,000 miles of transmission lines in the next five years. 

And the Federal Energy Regulatory Commission (FERC), which regulates interstate transmission networks, has ordered grid operators and utilities to consider GETs as part of recently mandated long-term transmission plans and as tools to streamline interconnection of clean energy projects now stuck in yearslong backlogs across much of the country. 

DLR systems, which can be deployed in a matter of months at less than 5 percent of the cost of replacing or rebuilding high-voltage power lines, are one of the quickest and cheapest options available. But realizing the large-scale benefits that DLR can deliver will take a lot more sensors on a lot more lines — and significantly more coordination between utilities and the transmission grid operators that manage energy markets across much of the country. 

Finding the extra grid headroom on windblown power lines

Even in pilot projects, DLR systems have yielded near-term grid benefits. In particular, they’ve helped solve a growing problem for many U.S. utilities: the rising grid congestion in parts of the country that are rich in wind power. 

Great River Energy (GRE), which operates 5,100 miles of transmission lines providing power to 27 member-owned cooperatives across Minnesota, installed four Heimdall sensors last year on one of its most congested power lines, said Priti Patel, the cooperative utility’s vice president and chief transmission officer. Like many other Midwestern states, Minnesota has a lot of wind farms — and ​“congestion typically follows wind,” she said. 

Congestion results when there’s not enough transmission capacity to deliver lower-cost power to where it’s in greatest demand, which forces utilities and grid operators to use power that’s closer but more costly instead. Congestion costs have risen steeply in the past few years, reaching an estimated $20.8 billion in 2022, according to analysis firm Grid Strategies — and much of the congestion is happening on grids with the most wind power. 

DLR is particularly well-suited to addressing these wind-related congestion problems. That’s because the technology can balance out competing factors that influence how hot (creeping toward maximum capacity) or cool (operating below capacity) a line really is. For example, when it’s windy out, wind turbines produce and send a lot of power onto various lines, heating them up. But those same high winds act to cool power lines, enabling them to safely sustain the increased load. Unlike static ratings, DLR systems can account for those nuances in real time, allowing grid operators to OK the higher power flows.

In the case of GRE’s single-line pilot, ​“we were able to realize capacity gains that exceeded our seasonal static rating by an average of over 40 percent,” Patel said. ​“That gave us some confidence to move forward with a broader implementation.”

But solving problems on one power line is just the start. Gathering more data from more power lines is an important next step. Transmission grids are networks, with power flowing between various connected lines. In that sense, the power capacity of the network is determined by the weakest links of its most constrained power lines. 

That interdependence makes it difficult to extrapolate the capacity gains from one DLR-equipped line to the network as a whole, Festervoll said. ​“With most of our projects we see a lot more than 40 percent” greater capacity compared to static ratings, he said. 

But there’s no way to guarantee how much greater the capacity of the network as a whole might be under different weather and wind conditions without deploying the sensors and collecting the data. ​“The point here is to measure what it is — to know,” he said. 

From knowing to doing 

With more complete knowledge comes the potential to act — namely, to start operating the transmission network in ways that more fully utilize the additional capacity that DLR systems reveal. 

For GRE, that requires integrating its DLR data not just into the energy-management-system (EMS) software that it and other transmission operators use, but into the systems of the Midcontinent Independent System Operator (MISO), which manages the transmission grids and energy markets in part or all of 15 U.S. states, including Minnesota, plus Canada’s Manitoba province. 

“We’re still in the process of integrating the software between Heimdall and GRE so we can bring the values into our EMS system,” Patel said. ​“Once those values get to us” — in early 2025 — ​“we’ll share that data with MISO.” 

That data-sharing is critical. While GRE operates its transmission grid, MISO is in charge of determining the day-to-day and hour-to-hour operations of power plants, wind farms, and other generation resources, Patel explained. 

MISO has ​“to look at what generators will stay on or shut down, both day-ahead and in real time,” she said. ​“To make those decisions,” grid operators must ​“have a pretty good expectation of demand and transmission constraints,” which can determine whether a wind farm is curtailed — ordered to reduce its output to avoid worsening grid congestion or causing grid overloads — or allowed to keep generating from hour to hour. 

Like other interstate grid operators, MISO is required to comply with regulations set by FERC. In 2021, the agency approved Order 881, which requires transmission-owning utilities to switch from using traditional static line ratings to seasonally adjusted ​“ambient-adjusted ratings,” or AARs, starting next year. 

AARs aren’t based on real-time sensor data like DLRs are. But Order 881 did require grid operators to ​“establish and maintain systems and procedures” that will ​“allow transmission owners that would like to use dynamic line ratings the ability to do so” — and MISO has been increasingly accepting DLR-derived data to inform its day-to-day operations as it moves toward meeting next year’s deadline for compliance.

“As we provide more real-time data into MISO around potential increased capacity on transmission — and as they gain confidence in this — that allows them to dispatch generation that may not have been dispatched before,” Patel said. That, in turn, ​“can provide low-cost power to customers.” 

From operating to planning 

All of this has to do with managing real-time grid operations. But in the longer term, DLR can also help utilities and grid operators plan the multibillion-dollar investments needed to expand U.S. power grids. 

That’s the task that AES, a major power generation owner that also operates regulated utilities in Ohio and Indiana, has undertaken with U.S.-based DLR technology company LineVision. In 2023, the companies installed 42 LineVision sensors on five power lines, the largest DLR deployment in the U.S. before GRE and Heimdall Power announced their project. Last month, AES and LineVision published a case study that highlighted the potential for DLR to guide grid investments in ways that could save a lot of money. 

The case study highlights the findings from two of the five lines equipped with DLR. With both lines, the first goal was to solve the ​“pain point of transmission capacity,” said Alexina Jackson, AES’s vice president of strategic development. ​“Let’s get a handle on that. Are we imposing scarcity on ourselves, or are we truly scarce?” 

The first line is located in an area where AES expects to see significant economic development and therefore a growing demand for power, which could require replacing it with a higher-capacity power cable — ​“reconductoring,” in utility lingo. But LineVision’s DLR sensors revealed that what appeared to be a capacity-constrained section of the grid, according to static rating methodology, was in fact capable of meeting those future needs. 

That meant AES could forgo plans to replace the line, which would have taken about two years and cost $590,000 per mile. The DLR deployment cost one-tenth of that and yielded its data in nine months — a good example of what the report characterized as a ​“no-regrets” use of the technology. 

In contrast, on the second line where LineVision installed DLR, the sensors revealed that static line ratings were actually overestimating its capacity to carry power. In other words, the technology revealed a constraint that traditional line-rating techniques may have missed. 

But the DLR data also revealed that this constraint was largely limited to a half-mile stretch in a ​“narrow, low-wind and high vegetation corridor” — a location where sagging lines present a particular danger. With that information in hand, AES plans to reconductor only that one half mile with higher-capacity power cables, rather than the entire line — a targeted approach that will take about half the time and cost one-quarter as much as full reconductoring would.

This particular line is relatively low-voltage, of the ​“bread-and-butter” type that serves much of the Midwest, Jackson said. Such lower-voltage lines can end up becoming the weakest link in a transmission network as utilities like AES incorporate ​“more solar and wind, and put in these pipes — 345-kV or larger transmission lines that are a focus of a lot of the conversation today — and send more energy into those local systems.” 

That highlights the value of DLR ​“not just in operations but in planning, because that’s the key rub to advancing on interconnection issues,” Jackson said. Today, swaths of U.S. transmission grids are unable to rapidly connect proposed clean energy projects due to a lack of capacity. 

If utilities and grid operators don’t incorporate DLR and other grid-enhancing technologies as they search for the most cost-effective way to expand those grids, then ​“we’re not addressing a key blocker,” she said. 

The state regulators in charge of approving utility grid investments are the next party that needs to buy into that value, she said. The first step is to convince regulators that this increased visibility is worth the cost of deploying the DLR tech. The next step is to convince regulators that the grid plans utilities develop using that data are as safe and cost-effective as the ones they design via traditional methods. 

“Let’s assemble that record, and take those points of value, and then go to the regulator and say, ​‘We want your support,’” Jackson said.